This thesis proposes a stochastic algorithm for managing the variability of wind energy by incorporating hourly demand response in the day... Show moreThis thesis proposes a stochastic algorithm for managing the variability of wind energy by incorporating hourly demand response in the day-ahead scheduling in power systems. Monte Carlo simulation with Latin hypercube sampling technique is applied to represent the uncertainties of wind energy via different wind scenarios. Demand response has several physical and operating constraints to be considered into the stochastic security-constrained unit commitment (SCUC) for economic, reliability, and security purposes. Benders decomposition method is applied to decompose the large-scale complex stochastic SCUC problem into several tractable problems. Different case studies are analyzed in this thesis to demonstrate the benefits of applying DR to the proposed day-ahead scheduling model with variable wind energy. M.S. in Electrical Engineering, May 2015 Show less
